Mathematical Modeling in Experimental NutritionAndrew J. Clifford, Hans-Georg Müller Springer Science & Business Media, 31 ago 1998 - 426 páginas Nutrients have been recognized as essential for maximum growth, successful reproduction, and infection prevention since the 1940s; since that time, the lion's share of nutrient research has focused on defining their role in these processes. Around 1990, however, a major shift began in the way that researchers viewed some nutrients particularly the vitamins. This shift was motivated by the discovery that modest declines in vitamin nutritional status are associated with an increased risk of ill-health and disease (such as neural tube defects, heart disease, and cancer), especially in those populations or individuals who are genetically predisposed. In an effort to expand upon this new understanding of nutrient action, nutritionists are increasingly turning their focus to the mathematical modeling of nutrient kinetic data. The availability of suitably-tagged (isotope) nutrients (such as B-carotene, vitamin A, folate, among others), sensitive analytical methods to trace them in humans (mass spectrometry and accelerator mass spectrometry), and powerful software (capable of solving and manipulating differential equations efficiently and accurately), has allowed researchers to construct mathematical models aimed at characterizing the dynamic and kinetic behavior of key nutrients in vivo in humans at an unparalleled level of detail. |
Índice
Balancing Needs Efficiency and Functionality in the Provision of Modeling | 3 |
Heidi A Johnson | 35 |
SingleInput MultipleOutput Study Using the SAAM II Software | 59 |
System | 79 |
The Mathematics behind Modeling | 115 |
Distributing Working Versions of Published Mathematical Models | 131 |
Measurement Error and Dietary Intake | 139 |
Statistical Models for Quantitative Bioassay | 147 |
Advances in the Modeling of Stable Isotope Data | 253 |
Key Features of Copper versus Molybdenum Metabolism Models in Humans | 271 |
Insights into Bone Metabolism from Calcium Kinetic Studies in Children | 283 |
Modeling of Energy Expenditure and Resting Metabolic Rate during Weight | 293 |
Development and Application of a Compartmental Model of 3Methyhistidine | 303 |
Modeling Ruminant Digestion and Metabolism | 325 |
Designing a Radioisotope Experiment Using a Dynamic Mechanistic Model | 345 |
Protocol Development for Biological Tracer Studies | 363 |
Statistical Issues in Assay Development and Use | 173 |
Statistical Tools for the Analysis of Nutrition Effects on the Survival | 191 |
Development of a Compartment Model Describing the Dynamics of Vitamin | 207 |
Compartmental Models of Vitamin A and BCarotene Metabolism in Women | 225 |
The Dynamics of Folic Acid Metabolism in an Adult Given a Small Tracer | 239 |
Plasma Source Mass Spectrometry in Experimental Nutrition | 379 |
| 397 | |
| 411 | |
Otras ediciones - Ver todo
Mathematical Modeling in Experimental Nutrition Andrew J. Clifford,Hans-Georg Müller Vista previa restringida - 2013 |
Mathematical Modeling in Experimental Nutrition Andrew J. Clifford,Hans-Georg Müller No hay ninguna vista previa disponible - 2013 |
Mathematical Modeling in Experimental Nutrition Andrew J. Clifford,Hans-Georg Müller No hay ninguna vista previa disponible - 2013 |
Términos y frases comunes
AACD AAPB absorption accelerator mass spectrometry ACSL amino acid analysis assay biological blood calcium calculated cell Clin Cobelli coefficients compartment compartmental model components concentration copper curve described determined deuterium dietary energy expenditure enrichment equations error erythrocyte excretion FA+BF FDAA feces flooding dose folate fractional function glucose humans ICP-MS identifiability infant input intake intracellular pool isotope ratio isotope tracer isotopomers kinetic model labeled lactation leucine levels linear liver mass spectrometry Mathematical Modeling measurement metabolism method model prediction model structure molybdenum Müller muscle protein nmol nmol/kg diet nonlinear Nutr nutrient oxidation parameter estimates PBAA plasma population precision protein pool protein synthesis proteolysis quantitative rats recycling regression retinol retinyl esters SAAM sample serum shown in Figure Simulation specific radioactivity ẞC stable isotope statistical studies tissue tracer tRNA Turnlund urinary urine values variability vitamin WBFSR weight WinSAAM zinc µmol
Referencias a este libro
Handbook of Elemental Speciation II: Species in the Environment ..., Volumen 2 Joseph A. Caruso,Helen Crews,Klaus G. Heumann Vista previa restringida - 2005 |
Handbook of Elemental Speciation II: Species in the Environment ..., Volumen 2 Joseph A. Caruso,Helen Crews,Klaus G. Heumann Vista previa restringida - 2005 |
